A spacecraft, aircraft, ground-based platform, or other object may have an unknown orientation (also known as attitude, i.e., angle of rotation in one or more dimensions relative to a reference). One way to determine the orientation of the object is to acquire one or more images of a starfield seen by the object, analyze the images, and compare the results to known starfield data (stored in, e.g., an on-board or remote database). By identifying known stars and noting their positions in the starfield relative to the object, the orientation of the object may be derived.
Current star-tracking systems and methods acquire a large number of images of the starfield (from, e.g., a digital camera on board the object) and store the images in computer memory. The images are averaged, either as they are acquired or after acquisition of all the images, to improve their quality (by, e.g., removing noise). These prior-art systems and methods require a large amount of memory to store the images and a large amount of processing power to average or otherwise process the images.
A star-tracking system may be exposed to high amounts of ionizing radiation, however, and the circuits and memory therein must be specially hardened to protect against computational and memory errors caused by, e.g., particle radiation and/or electromagnetic radiation. Large radiation-hardened (“rad-hard”) memory and circuits may be prohibitively expensive and, when used in a star-tracking system, may limit the size of the starfield image stored and/or the speed and amount of image processing possible. This limit may affect the accuracy achievable with the star-tracking system. Furthermore, some systems may have severe power constraints, and the processing required to analyze the images may consume an unacceptable amount of power.
A need therefore exists for a star-tracking system that is capable of increased accuracy of measurement and that uses available rad-hard memory and processing power more efficiently while consuming less power.